edibnb <- dsbox::edibnb
glimpse(edibnb)Rows: 13,245
Columns: 10
$ id <dbl> 15420, 24288, 38628, 44552, 47616, 48645, 51505, …
$ price <dbl> 80, 115, 46, 32, 100, 71, 175, 150, 139, 190, 85,…
$ neighbourhood <chr> "New Town", "Southside", NA, "Leith", "Southside"…
$ accommodates <dbl> 2, 4, 2, 2, 2, 3, 5, 5, 6, 10, 2, 4, 3, 2, 2, 4, …
$ bathrooms <dbl> 1.0, 1.5, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 2.0,…
$ bedrooms <dbl> 1, 2, 0, 1, 1, 1, 2, 3, 4, 4, 1, 1, 1, 1, 1, 2, 1…
$ beds <dbl> 1, 2, 2, 1, 1, 2, 3, 4, 5, 7, 1, 1, 1, 1, 1, 2, 1…
$ review_scores_rating <dbl> 99, 92, 94, 93, 98, 97, 100, 92, 96, 99, 77, 98, …
$ number_of_reviews <dbl> 283, 199, 52, 184, 32, 762, 7, 28, 222, 142, 14, …
$ listing_url <chr> "https://www.airbnb.com/rooms/15420", "https://ww…
summary(edibnb) id price neighbourhood accommodates
Min. : 15420 Min. : 0.00 Length:13245 Min. : 1.000
1st Qu.:13279107 1st Qu.: 49.00 Class :character 1st Qu.: 2.000
Median :20171841 Median : 75.00 Mode :character Median : 3.000
Mean :20077242 Mean : 97.21 Mean : 3.541
3rd Qu.:27397925 3rd Qu.:110.00 3rd Qu.: 4.000
Max. :36066014 Max. :999.00 Max. :19.000
NA's :199
bathrooms bedrooms beds review_scores_rating
Min. :0.000 Min. : 0.000 Min. : 0.000 Min. : 20.00
1st Qu.:1.000 1st Qu.: 1.000 1st Qu.: 1.000 1st Qu.: 93.00
Median :1.000 Median : 1.000 Median : 2.000 Median : 97.00
Mean :1.226 Mean : 1.583 Mean : 2.032 Mean : 95.02
3rd Qu.:1.000 3rd Qu.: 2.000 3rd Qu.: 3.000 3rd Qu.: 99.00
Max. :9.000 Max. :13.000 Max. :30.000 Max. :100.00
NA's :12 NA's :4 NA's :15 NA's :2177
number_of_reviews listing_url
Min. : 0.00 Length:13245
1st Qu.: 2.00 Class :character
Median : 12.00 Mode :character
Mean : 37.73
3rd Qu.: 45.00
Max. :773.00
edibnb <- edibnb |>
mutate(
neighbourhood = fct_reorder(
neighbourhood,
review_scores_rating,
.fun = median)
) |>
filter(!is.na(neighbourhood))